RFOP: Rethinking Fusion and Orthogonal Projection for Face-Voice Association
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arXiv
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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866911298082570240 |
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| author | Hannan, Abdul Malik, Furqan Jabbar, Hina Sadiq, Syed Suleman Noman, Mubashir |
| author_facet | Hannan, Abdul Malik, Furqan Jabbar, Hina Sadiq, Syed Suleman Noman, Mubashir |
| contents | Face-voice association in multilingual environment challenge 2026 aims to investigate the face-voice association task in multilingual scenario. The challenge introduces English-German face-voice pairs to be utilized in the evaluation phase. To this end, we revisit the fusion and orthogonal projection for face-voice association by effectively focusing on the relevant semantic information within the two modalities. Our method performs favorably on the English-German data split and ranked 3rd in the FAME 2026 challenge by achieving the EER of 33.1. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2512_02860 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | RFOP: Rethinking Fusion and Orthogonal Projection for Face-Voice Association Hannan, Abdul Malik, Furqan Jabbar, Hina Sadiq, Syed Suleman Noman, Mubashir Computer Vision and Pattern Recognition Face-voice association in multilingual environment challenge 2026 aims to investigate the face-voice association task in multilingual scenario. The challenge introduces English-German face-voice pairs to be utilized in the evaluation phase. To this end, we revisit the fusion and orthogonal projection for face-voice association by effectively focusing on the relevant semantic information within the two modalities. Our method performs favorably on the English-German data split and ranked 3rd in the FAME 2026 challenge by achieving the EER of 33.1. |
| title | RFOP: Rethinking Fusion and Orthogonal Projection for Face-Voice Association |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2512.02860 |